The above mentioned probability of 1 over \(40\,000\)  corresponds to the infamous \(p\) -value in the framework of frequentist null hypothesis significance testing [1]}. Famously, on the frequentist conception of probability it is not possible to assign probabilities to hypotheses since they are either true or false (i.e. they are no random variables).The frequentist interpretation estimates the probability of an event \(x\)  by the relative frequency of its occurrence. Hence, there needs to be a repeatable process, \(X\) , with various possible outcomes. To test a hypothesis needs therefor a detour. The \(p\) -value is defined as the probability to get the observed (or more extreme) data under the assumption that the so called null hypothesis, \(H_0\) , is true. In the above case the null hypothesis corresponds to the validity of the standard model.
